Text-to-Image
MiniMax H3
Diffusers
Safetensors
English
image-to-image
image-editing
image-generation
Instructions to use MiniMaxAI/MiniMax-H3-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MiniMaxAI/MiniMax-H3-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MiniMaxAI/MiniMax-H3-Image", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Update readme for LightX2V infer.
#14
by lightx2v - opened
README.md
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@@ -155,6 +155,7 @@ We recommend the following inference frameworks to serve the model:
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- [SGLang](https://docs.sglang.io/) - see [cookbook](https://docs.sglang.io/cookbook/diffusion/MiniMax/MiniMax-H3-Image)
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- [vLLM-Omni](https://github.com/vllm-project/vllm-omni) - see [vllm-omni recipe](https://recipes.vllm.ai/MiniMaxAI/MiniMax-H3-Image)
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- [diffusers](https://github.com/huggingface/diffusers) - see [diffusers docs](https://huggingface.co/docs/diffusers/main/en/api/pipelines/minimax_h3_image)
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- [ComfyUI](https://github.com/Comfy-Org/ComfyUI) - see [Comfy tutorial](https://docs.comfy.org/tutorials/image/minimax/minimax-h3-image); use [T2I template](https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_minimax_h3_image_t2i.json) / [Edit template](https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_minimax_h3_image_edit.json)
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--num-gpus 4 --ulysses-degree 4
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```
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#### Request parameters
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Text-to-image requests are JSON sent to `/v1/images/generations`. Image editing requests send
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- [SGLang](https://docs.sglang.io/) - see [cookbook](https://docs.sglang.io/cookbook/diffusion/MiniMax/MiniMax-H3-Image)
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- [vLLM-Omni](https://github.com/vllm-project/vllm-omni) - see [vllm-omni recipe](https://recipes.vllm.ai/MiniMaxAI/MiniMax-H3-Image)
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- [LightX2V](https://github.com/ModelTC/LightX2V) - see [Usage guide](https://github.com/ModelTC/LightX2V/tree/main/scripts/minimax_h3_image)
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- [diffusers](https://github.com/huggingface/diffusers) - see [diffusers docs](https://huggingface.co/docs/diffusers/main/en/api/pipelines/minimax_h3_image)
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- [ComfyUI](https://github.com/Comfy-Org/ComfyUI) - see [Comfy tutorial](https://docs.comfy.org/tutorials/image/minimax/minimax-h3-image); use [T2I template](https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_minimax_h3_image_t2i.json) / [Edit template](https://github.com/Comfy-Org/workflow_templates/blob/main/templates/image_minimax_h3_image_edit.json)
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--num-gpus 4 --ulysses-degree 4
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```
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#### LightX2V Deployment
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See the [LightX2V MiniMax-H3-Image guide](https://github.com/ModelTC/LightX2V/tree/main/scripts/minimax_h3_image) for complete usage instructions.
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Update lightx2v_path, model_path, and GPU settings in the cache-generation and server startup scripts. Run the following commands from the LightX2V repository root.
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First, generate the AdaLN cache:
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```bash
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bash tools/cache_minimax_h3_adaln/run_cache_minimax_h3_image_adaln.sh
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```
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Skip this step if a matching cache already exists. The same cache can be reused for single-GPU and multi-GPU serving.
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Start the server on one GPU:
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```bash
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bash scripts/minimax_h3_image/server/start_server.sh
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```
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For lower latency, start the server on four GPUs with sequence parallelism:
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```bash
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bash scripts/minimax_h3_image/server/start_server_sp4.sh
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```
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After model loading, send a request from another terminal:
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```bash
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python scripts/minimax_h3_image/server/post_t2i.py
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python scripts/minimax_h3_image/server/post_i2i.py
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```
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#### Request parameters
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Text-to-image requests are JSON sent to `/v1/images/generations`. Image editing requests send
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